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Banking is digitizing rapidly, especially in the use of digital and mobile devices to access bank services and make payments, thereby enhancing the convenience and service for the banking customer. These advances, however, have created significant opportunities for the perpetrators of fraud and financial crime, with estimates of losses to cyber-crime ranging from a few hundred million up to a trillion dollars each year. The increasingly sophisticated techniques used by cyber criminals — including undetected malware and unauthorized access to mobile devices and sensitive data — have led financial services organizations to pursue new approaches to preventing and detecting such activities.

Most cyber-attacks involve the loss of confidential information. As new products are introduced with new channels for distribution, new vulnerabilities arise and banks must continually develop new techniques to address them.

The challenge for banks and other financial services organizations is considerable as they try to balance the increasing demands of their customers and stay ahead of their competitors in the digital marketplace. They must be able to demonstrate to consumers that they have adequate safeguards in place to protect confidential information (and, ultimately, consumers’ assets). They also need to demonstrate to regulators they have active programs in place to prevent financial crime, with controls that are robustly enforced and standardized across business units and geographies. And, finally, banks need to demonstrate to shareholders that they can manage the monetary and financial risks associated with financial crime.

In their efforts to battle cyber-crime, a central concern for banks is the management and monitoring of vast quantities of data. Banks feed data from many sources into centralized monitoring systems, but maintaining the quality of data in terms of accuracy, timeliness and other factors is increasingly difficult. Accenture’s research shows that just over half of financial services organizations have a single view of their customers, and only about half have a single system to comply with anti-money laundering (AML) directives. Only about 60 percent have a single system for sanctions screening.

To help prevent and detect financial crime, banks need both an integrated (and timely) data set and the ability to bring sophisticated analytics to bear on the data to generate useful insights. We see three major elements that comprise this capability:

Enhanced data quality. Financial services firms use a variety of internal and external data sources to fight crime, but many firms – particularly universal banks operating in different regions and across different lines of business, using multiple systems and data sources – face data quality issues. To address the challenge, banks need to establish central data screening and reconciliation processes. Customer account data and transactional data used by different fraud management systems are collected from various sources. Screening and cleaning the data enhances the quality of the analysis and helps reduce the number of false positives, which take considerable time and effort to address. Banks should also improve their data governance, establishing clear lines of responsibility among business process owners, their technology counterparts and the fraud and financial crime data management teams.

Analytics to transform data into information, and information into insight. For most organizations, the problem is not the lack of data, but the lack of the right data. Data-driven decision-making – using Big Data – allows banks to gain a better understanding of the various physical, societal, financial and commercial aspects of their operating environment. This, in turn, improves the quality of decision-making, helping banks prevent financial crime, protect their reputations and create value by helping their customer-facing organizations do a better job of understanding the people with whom they do business.

Application of data visualization techniques. As the volume and complexity of data increase, key software providers such as SAS are adopting data visualization techniques allowing complex data to be viewed by business experts through a visual interface. This helps the experts look for visual patterns and identify inconsistencies. For example, once a customer account is opened, continuous monitoring occurs to flag any suspicious transactions or activities. A visual view of how transactions flow across multiple accounts helps investigators identify new patterns, and, when complex cases are investigated in more detail, visual clusters of the interrelated accounts assist in the analysis and identification of risks. Financial services organizations that work to achieve a single view of the customer to help detect and prevent financial crime may be able to reduce risks related to compliance and regulation, but they may also leverage their success to enhance their reputation and improve customer retention rates. By using big data technologies to provide centralized access to data, banks can employ analytics to obtain valuable insights and make informed decisions quickly and flexibly. Given the rapid evolution of financial crime and the ever-increasing stringency of regulatory requirements, banks and other financial services firms need this kind of agility and adaptability more than ever.